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Record W2745666302 · doi:10.3389/fneur.2017.00415

The Clinical Utility of Vestibular-Evoked Myogenic Potentials in the Diagnosis of Ménière’s Disease

2017· review· en· W2745666302 on OpenAlexafffund
Maxime Maheu, Jenny Marylin Alvarado-Umanzor, Audrey Delcenserie, François Champoux

Bibliographic record

VenueFrontiers in Neurology · 2017
Typereview
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada
KeywordsVestibular evoked myogenic potentialMeniere's diseaseMedicineVestibular systemDiseaseNeurosciencePhysical medicine and rehabilitationAudiologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Ménière's disease (MD) is a condition that has been proposed over 150 years ago, which involves audiological and vestibular manifestations, such as aural fullness, tinnitus, vertigo, and fluctuating hearing thresholds. Over the past few years, many researchers have assessed different techniques to help diagnose this pathology. Vestibular-evoked myogenic potential (VEMP) is an electrophysiological method assessing the saccule (cVEMP) and the utricule (oVEMP). Its clinical utility in the diagnosis of multiple pathologies, such as superior canal dehiscence, has made this tool a common method used in otologic clinics. The main objective of the present review is to determine the current state of knowledge of the VEMP in the identification of MD, such as the type of stimuli, the frequency tuning, and the interaural asymmetry ratio of the cVEMP and the oVEMP. Results show that the type of stimulation, the frequency sensitivity shift and the interaural asymmetry ratio (IAR) could be useful tool to diagnose and describe the evolution of MD. It is, however, important to emphasize that further studies are needed to confirm the utility of VEMP in the identification of MD in its early stage, using either bone-conduction vibration or air-conduction stimulation, which is of clinical importance when it comes to early intervention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.144
GPT teacher head0.401
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2017
Admission routes2
Has abstractyes

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